journal article·2015-02

Design of experiments for the development of poly(d,l-lactide-co-glycolide) nanoparticles loaded with Uncaria tomentosa

Ana Ferreira Ribeiro, Carina Torres Garruth Ferreira, Juliana Fernandes dos Santos, Lúcio Mendes Cabral, Valéria Pereira de Sousa

Journal of Nanoparticle Research· Volume 17· Issue 2
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Abstract

Polymeric nanoparticles have been shown to be effective carriers for natural substances that possess anticancer properties. Incorporation of these natural substances into polymeric nanoparticles increases targeting of these drugs, thus reducing side effects. Uncaria tomentosa (UT) is a Peruvian Amazon plant (existing in the Brazilian Amazon rainforest) that possesses promising anti-tumor activity. This paper describes the development of poly(d,l-lactide-co-glycolide) (PLGA) nanoparticles loaded with UT extract. The emulsion solvent evaporation method was utilized and the initial conditions were determined for the organic phase (OP) and the aqueous phase (AP). The influence of surfactant (type and concentration), PLGA concentration and AP volume on nanoparticle size, polydispersity index (PI), and entrapment efficiency (EE) was determined using a fractional factorial design (FFD). In addition, the formulation was optimized using a Box–Behnken design. After the conditions were optimized, UT nanoparticles were obtained using an OP composed of an ethyl acetate:acetone (3:2) mixture which contained the UT alkaloids and PLGA, and an AP composed of a buffered solution of Poloxamer 188 (pH 7.5). The optimized formulation produced an EE of 64.6 %, a particle size of 107.4 nm and a PI of 0.163. The preliminary experiments provided important information regarding the behavior of the nanoparticulate system and the FFD used in this study greatly facilitated the selection of the most optimal conditions for formulation development.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Alkaloids: synthesis and pharmacology · Surfactants and Colloidal Systems · Advanced Drug Delivery Systems

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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